NoSQL for Data Science In Depth

NoSQL for Data Science In Depth

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 56m | 257 MB

Many organizations are turning to NoSQL databases to store large volumes of complex data, sparking an increased need for data scientists and analysts to understand non-relational data stores. If you’re a data scientist or business analyst who needs to work with NoSQL, then this course is for you. Learn about the differences between relational and NoSQL databases, review types of NoSQL databases, and see how to perform common data science tasks, including data preparation, exploration, and building and applying models.

The course begins with an introduction to NoSQL, and then delves into the specifics of document, wide-column, and graph databases. Learn key details for performing data preparation, exploration, and extraction for each type of NoSQL database. Review case studies that show how to use various NoSQL databases with popular data science tools, including the document database MongoDB, the wide-column database Cassandra, and the graph database Neo4j.

Topics include:

  • NoSQL compared to traditional relational databases
  • Performing common data science tasks
  • Preparing data with document databases
  • Manipulating data in NoSQL
  • Preparing, exploring, extracting, and model building
  • Working with document, wide-column, and graph databases
  • Reviewing case studies using MongoDB, Cassandra, and Neo4j
Table of Contents

What you should know
Exercise files

1. Why NoSQL?
The limits of relational databases
Types of NoSQL databases
Advantages of NoSQL databases
Performing data science tasks with NoSQL

2. Perform Common Data Science Tasks with NoSQL Databases
Preparing data
Exploring data
Building models
Applying models

3. Document Databases for Data Science
Document data models
JSON structures
Prepare data with document databases
Install Anaconda
Install MongoDB
Working with Jupyter
Explore data with document databases
Extract data with document databases
Perform quality checks
Index data with document databases
Data frames in MongoDB
Tips for using document databases for data science

4. Wide-Column Databases for Data Science
Wide-column data models
Prepare data with wide-column databases
Install the Java Development Kit
Install Cassandra
Prepare data for Cassandra
Load data into Cassandra
Cassandra and Spark
Tips for using wide-column databases for data science

5. Graph Databases for Data Science
Graph data models
Key graphi concepts
Prepare data with graph databases
Install Neo4j
Explore data with graph databases
Extract data with graph databases
Tips for using graph databases for data science

Next Steps